Gaël Varoquaux
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Latest posts
misc personnal programming science
Technical discussions are hard; a few tips
This post discuss the difficulties of communicating while developing open-source projects and tries to gives some simple advice.
A large software project is above all a social exercise in which technical experts try to reach good decisions together, for instance on github pull requests. But communication is difficult, in …
in programming · 28 May 2020 Read
Jean Dechoux, June 13rd 1923 – Feb 9th 2020
Jean Dechoux was born between the first and the second world wars, in a small French town, close to Germany. His family was that of poor farmers, who would work in coal mines to make up for the small size of their crops.
He grew to become a pulmonologist, heading …
in personnal · 16 February 2020 Read
Survey of machine-learning experimental methods at NeurIPS2019 and ICLR2020
A simple survey asking authors of two leading machine-learning conferences a few quantitative questions on their experimental procedures.
How do machine-learning researchers run their empirical validation? In the context of a push for improved reproducibility and benchmarking, this question is important to develop new tools for model comparison. We …
in science · 22 January 2020 Read
2019: my scientific year in review
My current research spans wide: from brain sciences to core data science. My overall interest is to build methodology drawing insights from data for questions that have often been addressed qualitatively. If I can highlight a few publications from 2019 [1], the common thread would be computational statistics, from dirty …
in science · 05 January 2020 Read
Comparing distributions: Kernels estimate good representations, l1 distances give good tests
Given two set of observations, are they drawn from the same distribution? Our paper Comparing distributions: l1 geometry improves kernel two-sample testing at the NeurIPS 2019 conference revisits this classic statistical problem known as “two-sample testing”.
This post explains the context and the paper with a bit of hand …
in science · 08 December 2019 Read
Getting a big scientific prize for open-source software
An important acknowledgement for a different view of doing science: open, collaborative, and more than a proof of concept.
A few days ago, Loïc Estève, Alexandre Gramfort, Olivier Grisel, Bertrand Thirion, and myself received the “Académie des Sciences Inria prize for transfer”, for our contributions to the scikit-learn project …
in programming · 01 December 2019 Read
2018: my scientific year in review
From a scientific perspective, 2018 [1] was once again extremely exciting thank to awesome collaborators (at Inria, with DirtyData, and our local scikit-learn team). Rather than going over everything that we did in 2018, I would like to give a few highlights: We published major work using machine learning to …
in science · 03 January 2019 Read
A foundation for scikit-learn at Inria
We have just announced that a foundation will be supporting scikit-learn at Inria [1]: scikit-learn.fondation-inria.fr
This is an exciting turn for us, because it enables us to receive private funding. As a result, we will be able to have secure employment for some existing core …
in programming · 17 September 2018 Read
Sprint on scikit-learn, in Paris and Austin
Two weeks ago, we held a scikit-learn sprint in Austin and Paris. Here is a brief report, on progresses and challenges.
Several sprints
We actually held two sprint in Austin: one open sprint, at the scipy conference sprints, which was open to new contributors, and one core sprint, for more …
in programming · 01 August 2018 Read
Our research in 2017: personal scientific highlights
In my opinion the scientific highlights of 2017 for my team were on multivariate predictive analysis for brain imaging: a brain decoder more efficient and faster than alternatives, improvement clinical predictions by predicting jointly multiple traits of subjects, decoding based on the raw time-series of brain activity, and a personnal …
in science · 31 December 2017 Read
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